Abstract: In recent years, following the development of sensor and computer techniques, it is favored by many fields, i.e. automatic drive, intelligent home, etc., which the deep learning based ...

Abstract: The performance of distributed applications has long been hindered by network communication, which has emerged as a significant bottleneck. At the core of this issue, the many-to-one incast ...

Aquablue opened its new headquarters in Morristown, New Jersey, having expanded by 40%+ in 2025, strengthening their leadership and operational capabilities. As enterprises scale and digital ...

Abstract: Towards building online analytical services on big heterogeneous graphs, we study the problem of the multithreading graph aggregation. The purpose is to exploit the thread-level parallelism ...

Abstract: Federated learning (FL), as a promising machine learning paradigm for large-scale distributed data, faces two security challenges of privacy and robustness: the transmitted model updates ...

Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...

SINGAPORE, SINGAPORE, SINGAPORE, March 1, 2026 /EINPresswire.com/ — As the generative AI market hurtles toward a projected $1 trillion valuation by the end of 2026 ...

Abstract: There exist various categories of uncertain information, and their corresponding methods of aggregation may also vary. At present, there exists a dearth of specifically tailored techniques ...

Abstract: Multipoint dynamic aggregation (MPDA) is a multirobot task allocation problem, which requires the collaborative scheduling of multiple robots to complete time-varying tasks distributed on a ...

Abstract: Hierarchical federated learning shows excellent potential for communication-computation trade-offs and reliable data privacy protection by introducing edge-cloud collaboration. Considering ...